The next-generation Open Targets Platform: reimagined, redesigned, rebuilt
Open accessAbstract
The Open Targets Platform (https://platform.opentargets.org/) is an open source resource to systematically assist drug target identification and prioritisation using publicly available data. Since our last update, we have reimagined, redesigned, and rebuilt the Platform in order to streamline data integration and harmonisation, expand the ways in which users can explore the data, and improve the user experience. The gene–disease causal evidence has been enhanced and expanded to better capture disease causality across rare, common, and somatic diseases. For target and drug annotations, we have incorporated new features that help assess target safety and tractability, including genetic constraint, PROTACtability assessments, and AlphaFold structure predictions. We have also introduced new machine learning applications for knowledge extraction from the published literature, clinical trial information, and drug labels. The new technologies and frameworks introduced since the last update will ease the introduction of new features and the creation of separate instances of the Platform adapted to user requirements. Our new Community forum, expanded training materials, and outreach programme support our users in a range of use cases.
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By assembling heterogeneous data types such as those included in Pharos, an ML-ready KG can capture data from major areas specific for human protein-coding genes: phenotype and disease, pathways, and interactions.
“By assembling heterogeneous data types such as those included in Pharos (22), an ML-ready KG can capture data from major areas specific for human protein-coding genes: phenotype and disease, pathways, and interactions.”
From Artificial Intelligence for Drug Discovery: Are We There Yet? (2024) · cites this paper as [22]
The Introduction sections on enhanced target–disease evidence and improving target characterisation describe Open Targets integrating disease and phenotype evidence, pathways, and molecular interactions. But the citation is attached to Pharos, while this paper describes Open Targets; our copy does not establish that Pharos contains those data types or that assembling them produces an ML-ready knowledge graph. Page numbers were not available in our copy. (LLM, conf=0.83)
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Artificial Intelligence for Drug Discovery: Are We There Yet?
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“Automated systems that digest large sets of data using named entity recognition, NER (18), are an integral part of public domain databases, for example, DISEASES for gene-disease associations (19); STRING for protein-protein interactions (20); and OpenTargets (21) and Pharos (22) for complex disease-protein-drug annot…”
BackgroundPapier, K., Atkins, J. R., Tong, T. Y. N., Gaitskell, K., Desai, T., Ogamba, C. F., Parsaeian, M., Reeves, G. K., Mills, I. G., Key, T. J., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-48017-6 · Cited by 97 · see citing works
- Authors
- Ochoa, D., Hercules, A., Carmona, M., Suveges, D., Baker, J., Malangone, C., Lopez, I., Miranda, A., Cruz-Castillo, C., Fumis, L., Bernal-Llinares, M., Tsukanov, K., Cornu, H., Tsirigos, K., Razuvayevskaya, O., Buniello, A., Schwartzentruber, J., Karim, M., Ariano, B., Martinez Osorio, R. E., Ferrer, J., Ge, X., Machlitt-Northen, S., Gonzalez-Uriarte, A., Saha, S., Tirunagari, S., Mehta, C., Roldán-Romero, J. M., Horswell, S., Young, S., Ghoussaini, M., Hulcoop, D. G., Dunham, I., & McDonagh, E. M.
- Affiliations
- European Bioinformatics Institute (GB)
- Open Targets, Wellcome Genome Campus , Hinxton, Cambridgeshire CB10 1SD, UK
- Wellcome Sanger Institute (GB)
- GlaxoSmithKline plc, GSK Medicines Research Centre , Gunnels Wood Road, Stevenage, SG1 2NY, UK
- GlaxoSmithKline (United Kingdom) (GB)
- Corresponding author
- Ochoa, David
- McDonagh, Ellen M
- ORCID
- Ochoa, David
- Hercules, Andrew
- Carmona, Miguel
- Baker, Jarrod
- Cruz-Castillo, Carlos
- Fumis, Luca
- Bernal-Llinares, Manuel
- Tsukanov, Kirill
- Cornu, Helena
- Tsirigos, Konstantinos
- Razuvayevskaya, Olesya
- Buniello, Annalisa
- Schwartzentruber, Jeremy
- Karim, Mohd
- Ariano, Bruno
- Ge, Xiangyu
- Saha, Shyamasree
- Tirunagari, Santosh
- Horswell, Stuart
- Young, Sarah
- Ghoussaini, Maya
- Hulcoop, David G
- Dunham, Ian
- McDonagh, Ellen M
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2022-11-18
- Volume
- 51
- Issue
- D1
- Pages
- D1353-D1359
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC9825572
- OpenAlex
- W4309306035
- Cited by
- 432
- References
- 44
- Citations by year
- 2026: 108 · 2025: 136 · 2024: 133 · 2023: 55
- FWCI
- 46.15
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Wellcome Trust (206194)
- Open Targets
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- Open Targets Platform, drug target prioritization, drug target identification, genetic constraints, AlphaFold structure prediction, clinical trial data, drug labels
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